Amc Setup Calibration Stack
NVIDIA/skills
Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose.
Prepare this repository's mesh-to-USD generation, structural validation, and Isaac Sim drop-test environment.
Install Mesh To Usd Setup
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-setup -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-setup --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/mesh-to-usd-setup .claude/skills/mesh-to-usd-setup && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "mesh-to-usd-setup" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-setup into .claude/skills/mesh-to-usd-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-setup", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-setupType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-setup -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-setup --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.codex/skills/mesh-to-usd-setup .agents/skills/mesh-to-usd-setup && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "mesh-to-usd-setup" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-setup into .agents/skills/mesh-to-usd-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-setup", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-setup -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-setup --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.codex/skills/mesh-to-usd-setup .cursor/skills/mesh-to-usd-setup && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "mesh-to-usd-setup" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-setup into .cursor/skills/mesh-to-usd-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-setup", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/nvidia-isaac/video_to_data.git --path .codex/skills/mesh-to-usd-setup--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-setup -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-setup --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.codex/skills/mesh-to-usd-setup .gemini/skills/mesh-to-usd-setup && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "mesh-to-usd-setup" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-setup into .gemini/skills/mesh-to-usd-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-setup", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-setupInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-setup -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .github/skills && cp -r skills-src/.codex/skills/mesh-to-usd-setup .github/skills/mesh-to-usd-setup && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "mesh-to-usd-setup" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-setup into .github/skills/mesh-to-usd-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-setup", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-setup -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-setup --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.codex/skills/mesh-to-usd-setup .opencode/skills/mesh-to-usd-setup && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "mesh-to-usd-setup" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-setup into .opencode/skills/mesh-to-usd-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-setup", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
mesh-to-usd-setup- GitHub stars
- 856
- Token cost
- ~1.1k tokens
- SKILL.md length
- 440 words
- Files
- 2
- Skills in repo
- 13
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Prepare this repository's mesh-to-USD generation, structural validation, and Isaac Sim drop-test environment.
- Works in 6 steps: All host --help commands above succeed. → The selected input contract exists and… → v2d_hoi_mesh_to_usd and… → …
- A user asks to build the mesh-to-USD images
- SKILL.md covers Act before asking, Establish the checkout, Determine the input contract and Build only missing images, plus 1 more section
- Calls python, docker and git
What it does
Mesh To Usd Setup is an agent skill from nvidia-isaac/video_to_data. Prepare this repository's mesh-to-USD generation, structural validation, and Isaac Sim drop-test environment. Use when a user asks to build the mesh-to-USD images, verify Docker/GPU access, prepare FoundationPose support calibration, check model weights, validate a standalone GLB or exported HOI sequence input, or make the checkout ready before generating a rigid USD.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).
It sits in DevOps & Cloud, covering Performance reviews and Containers. It works with Docker. The repository describes itself as: Nvidia Isaac Video to Data Pipeline.
When your agent uses it
- A user asks to build the mesh-to-USD images
- Verify Docker/GPU access
- Prepare FoundationPose support calibration
- Check model weights
Example prompts
- “/mesh-to-usd-setup”
Requirements
- Python 3
- Docker
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- All host --help commands above succeed.
- The selected input contract exists and every required file is nonempty.
- v2d_hoi_mesh_to_usd and v2d_hoi_mesh_to_usd_validator exist.
- GPU 0 is visible inside the generator image
- Cross-mesh mode, when selected, has the FoundationPose image, populated
- The user has explicitly accepted the EULA or will provide
What it can do on your machine
Read from SKILL.md and the folder at commit 193382a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
pythondockergit
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use docker and git, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Mesh To Usd Setup loads about 1.1k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 440 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 440 words (~1,147 tokens).
“Prepare the workflow and prove that the requested input mode is runnable. Work from reconstruction/; keep Isaac Sim, OpenUSD, CoACD, and FoundationPose dependencies inside their existing containers.”
- name
- mesh-to-usd-setup
Files
SKILL.md and 1 other file in .codex/skills/mesh-to-usd-setup of nvidia-isaac/video_to_data.
- SKILL.md
- agents/openai.yaml
Open the folder on GitHubat commit 193382a
Compare with similar skills
Mesh To Usd Setup next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Mesh To Usd Setup this skillnvidia-isaac/video_to_data | 856 | — | ~1.1k | Automated safety check: Pass | Custom licence | |
| Amc Setup Calibration StackNVIDIA/skills | 3.5k | — | ~3.9k | Automated safety check: Notes | Apache-2.0 | |
| Iron Proxy Gateway for NanoClawnanocoai/nanoclaw | 31k | — | ~4.6k | Automated safety check: Notes | MIT | |
| GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb | 6.7k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| Senior DevOps Toolkitmaslennikov-ig/claude-code-orchestrator-kit | 260 | 6 repos | ~1.1k | Automated safety check: Notes | Custom licence | |
| LangBot Deployment Guidelangbot-app/LangBot | 18k | — | ~1.2k | Automated safety check: Notes | Apache-2.0 |
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Related
Works with
Categories
Questions about Mesh To Usd Setup
What does Mesh To Usd Setup do?
Prepare this repository's mesh-to-USD generation, structural validation, and Isaac Sim drop-test environment. Mesh To Usd Setup is an agent skill from nvidia-isaac/video_to_data. Prepare this repository's mesh-to-USD generation, structural validation, and Isaac Sim drop-test environment.
When should I use Mesh To Usd Setup?
Mesh To Usd Setup fits situations like: A user asks to build the mesh-to-USD images; verify Docker/GPU access; prepare FoundationPose support calibration; check model weights.
How do I install Mesh To Usd Setup in Claude Code?
Run `npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-setup -a claude-code`. Or copy the skill folder (.codex/skills/mesh-to-usd-setup in nvidia-isaac/video_to_data) into .claude/skills/mesh-to-usd-setup in your project. Claude Code loads it when a task matches its description.
How do I install Mesh To Usd Setup in Codex?
Run `npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-setup -a codex`. Or copy the skill folder (.codex/skills/mesh-to-usd-setup in nvidia-isaac/video_to_data) into .agents/skills/mesh-to-usd-setup in your project. Codex loads it when a task matches its description.
Can I use Mesh To Usd Setup in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-setup -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mesh-to-usd-setup, .gemini/skills/mesh-to-usd-setup, .github/skills/mesh-to-usd-setup and .opencode/skills/mesh-to-usd-setup in your project.
What does Mesh To Usd Setup need to run?
Going by SKILL.md and its folder, Mesh To Usd Setup needs the command-line tools its instructions call (python, docker and git). Our summary lists: Python 3; Docker.
Does Mesh To Usd Setup access the network?
SKILL.md contains no URLs. Its commands use docker and git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Mesh To Usd Setup safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Mesh To Usd Setup use?
Mesh To Usd Setup has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Mesh To Usd Setup use?
About 1.1k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Mesh To Usd Setup?
Skills that share tags, products or a category with Mesh To Usd Setup: Amc Setup Calibration Stack (NVIDIA/skills, 3.5k stars), Iron Proxy Gateway for NanoClaw (nanocoai/nanoclaw, 31k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars) and Senior DevOps Toolkit (maslennikov-ig/claude-code-orchestrator-kit, 260 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Mesh To Usd Setup?
nvidia-isaac (a GitHub organization) maintains it in nvidia-isaac/video_to_data, which has 856 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 8, 2026.
Source: nvidia-isaac/video_to_data on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.